June 2015

As a result of recent advances in MEMS/NEMS and systems biology, as well as the emergence of synthetic bacteria and lab/process-on-a-chip techniques, it is now possible to design chemical “circuits”, custom organisms, micro/nanoscale swarms of devices, and a host of other new systems at small length scales, and across multiple scales (e.g., micro to macro)

On 21 May 2015, volunteers from the IEEE Signal Processing Society participated in NextBC 2 Showcase and Awards Gala in Vancouver, British Columbia, Canada.

The IEEE Signal Processing Society (SPS) is honored to announce the elevation of 22 of its members to the grade of IEEE Senior Member. These members have demonstrated outstanding professional performance, exhibited professional maturity through long-term experience, and established themselves as leaders in their respective IEEE-designated fields of interest. Senior Member is the only membership grade that is eligible to be nominated for IEEE Fellow.

The Design and Implementation of Signal Processing Systems Technical Committee (DISPS TC) has the mission to promote and support activities of the IEEE Signal Processing Society in the areas of: i) design, development and implementation of signal processing systems; ii) design of algorithms with implementation in mind and iii) design of software tools and methodologies to support the design of signal processing systems.

For our June 2015 issue, we cover recent patents dealing with various applications of image inpainting. The section below covers patents granted recently for image segmentation, image enhancement, mobile authentication, texture analysis and image compression.

The IEEE Signal Processing Society is happy to announce the creation of the Women in Signal Processing Subcommittee! The subcommittee hopes to better serve, expand, and mobilize the female SPS membership base through tailored events, networking opportunities, workshops, and more. The group has established a LinkedIn page for communications. If you’d like to be involved, head over to their LinkedIn page and join the conversation!

The special issue of Proceedings of the IEEE in April is the first of two special issues providing an in-depth treatment of the subject of reconfigurable systems as enabled through advancements in the electrical engineering field, as well as the approaches we use to manage complexity in systems having millions of fixed and programmable elements. This issue serves as an immersion into the subject of reconfigurable systems, both for the purposes of gaining familiarity with essential theoretical elements, the key developments in the field, and the potential future directions (not just the next few years, but decades beyond the present).

The IEEE Signal Processing Society Chapter of the Year Award will be presented for the fifth time in 2016. The award will be presented annually to a Chapter that has provided their membership with the highest quality of programs, activities and services. The award will be presented annually in conjunction with the International Conference on Acoustics, Speech, and Signal Processing (ICASSP) to the Chapter’s representative. The award will consist of a certificate and a check in the amount of $1,000 to support local chapter activities. The winning Chapter will also be invited to publish an article in the IEEE Inside Signal Processing eNewsletter.

SPS has changed its nominating process for all Society Awards from paper awards to the major society awards. We now call for nominations from any society individual member, society committee, or society board. Nominations from individual members can be supported by up to two endorsement letters from two other individual members. The SPS Awards Board is now accepting nominations for the 2015 major SPS awards.

Machine learning, a subfield of computer science, has been widely applied in many areas from science to engineering to many interdisciplinary fields. Nature Reviews Genetics recently published an article that summarized machine learning applications in genetics and genomics, authored by University of Washington researchers Maxwell W. Libbrecht and William Stafford Noble. The topics of interest included supervised versus unsupervised learning, generative versus discriminative modeling, incorporating prior knowledge, handling heterogeneous data, feature selection, imbalanced class sizes, handling missing data, and modelling dependence among examples.